A method and apparatus are provided for enhanced performance in the presence of stationary position error signal (PES) outliers in a direct access storage device (DASD). A plurality of PES samples are obtained from a plurality of servo sectors around a track. Utilizing the PES samples, a normalized outlier value is computed for each of the plurality of servo sectors around the track. The computed normalized outlier values are sequentially stored and compared with a set threshold value. A stationary PES outlier is identified responsive to each stored outlier value being greater than the set threshold value. Each identified stationary PES outlier is utilized during predefined operations of the DASD. During a recalibration mode of the DASD, a different track for feedforward generation is selected to avoid an identified stationary PES outlier. When more than one stationary PES outlier is identified from the servo sectors around a track, then data from the track is reassigned to an alternate track and the flawed track is marked to avoid use for future data storage.
Legal claims defining the scope of protection, as filed with the USPTO.
1. A method for implementing enhanced performance in the presence of stationary position error signal (PES) outliers in a direct access storage device (DASD) comprising the steps of: obtaining a plurality of PES samples, said plurality of PES samples obtained from a plurality of servo sectors around a track; utilizing said PES samples, computing a normalized outlier value for said plurality of servo sectors; sequentially storing said computed normalized outlier values; comparing said sequentially stored normalized outlier values with a set threshold value; identifying a stationary PES outlier responsive to each said stored outlier value being greater than said set threshold value; and utilizing each said identified stationary PES outlier during predefined operations of the DASD.
2. A method for implementing enhanced performance in the presence of stationary position error signal (PES) outliers as recited in claim 1 wherein the step of obtaining said plurality of PES samples, said plurality of PES samples obtained from said plurality of servo sectors around said track includes the step of sequentially obtaining said plurality of PES samples during a plurality of revolutions around said track.
3. A method for implementing enhanced performance in the presence of stationary position error signal (PES) outliers as recited in claim 2 wherein the step of utilizing said PES samples, computing said normalized outlier value for said plurality of servo sectors includes the step of utilizing said PES samples, computing an averaged, normalized outlier value for said plurality of servo sectors for said plurality of revolutions around said track.
4. A method for implementing enhanced performance in the presence of stationary position error signal (PES) outliers as recited in claim 1 wherein the step of utilizing said PES samples, computing said normalized outlier value for said plurality of servo sectors includes the step of computing said normalized outlier value y(n) for said plurality of servo sectors represented by: y ( n ) x ( n 1) x ( n ) x ( n 1) x ( n ) , where n 1,2,3 , . . . , N, where x(n) represents said PES samples, n represents a sector index, and 1< n< N, where N represents a the total number of servo sectors around said track.
5. A method for implementing enhanced performance in the presence of stationary position error signal (PES) outliers as recited in claim 4 wherein the step of computing said normalized outlier value y(n) for said plurality of servo sectors represented by: y ( n ) x ( n 1) x ( n ) x ( n 1) x ( n ) , where n 1,2,3 , . . . , N, includes three add operations and two absolute value operations per said normalized outlier value y(n).
6. A method for implementing enhanced performance in the presence of stationary position error signal (PES) outliers as recited in claim 1 wherein the step of utilizing said PES samples, computing said normalized outlier value for said plurality of servo sectors includes the step of computing said normalized outlier value y(n) for said plurality of servo sectors represented by: y ( n ) x ( n 1) x ( n ) 2 x ( n 1) x ( n ) 2 , where n 1,2,3 , . . . , N, where x(n) represents said PES samples, n represents a sector index, and 1< n< N, where N represents a the total number of servo sectors around said track.
7. A method for implementing enhanced performance in the presence of stationary position error signal (PES) outliers as recited in claim 6 wherein the step of computing said normalized outlier value y(n) for said plurality of servo sectors represented by: y ( n ) x ( n 1) x ( n ) 2 x ( n 1) x ( n ) 2 , where n 1,2,3 , . . . , N, includes three add operations and two multiply operations per said normalized outlier value y(n).
8. A method for implementing enhanced performance in the presence of stationary position error signal (PES) outliers as recited in claim 1 wherein the step of sequentially storing said computed normalized outlier values includes the step of sequentially storing incremental normalized outlier values y(n) according to n in an indexed N-point vector Y, where n represents a sector index, and 1< n< N, where N represents a the total number of servo sectors around said track.
9. A method for implementing enhanced performance in the presence of stationary position error signal (PES) outliers as recited in claim 8 includes the step of incrementing n by one until n equals N.
10. A method for implementing enhanced performance in the presence of stationary position error signal (PES) outliers as recited in claim 1 wherein the step of comparing said sequentially stored normalized outlier values with said set threshold value includes the step of comparing said sequentially stored normalized outlier values with a predefined track pitch related value.
11. A method for implementing enhanced performance in the presence of stationary position error signal (PES) outliers as recited in claim 1 wherein the step of utilizing each said identified stationary PES outlier during predefined operations of the DASD includes the step of identifying a recalibration mode of the DASD.
12. A method for implementing enhanced performance in the presence of stationary position error signal (PES) outliers as recited in claim 11 includes the step of responsive to said identified recalibration mode of the DASD, selecting a different track for feedforward generation to avoid said identified stationary PES outlier.
13. A method for implementing enhanced performance in the presence of stationary position error signal (PES) outliers as recited in claim 1 wherein the step of utilizing each said identified stationary PES outlier during predefined operations of the DASD includes the step of restarting an error recovery process at beginning and using a projected PES value responsive to said identified stationary PES outlier.
14. A method for implementing enhanced performance in the presence of stationary position error signal (PES) outliers as recited in claim 1 wherein the step of utilizing each said identified stationary PES outlier during predefined operations of the DASD includes the step of identifying more than one stationary PES outlier and reassigning data from said track and labeling said track as bad.
15. Apparatus for implementing enhanced performance in the presence of stationary position error signal (PES) outliers in a direct access storage device (DASD) comprising: a PES classifier for performing a nonlinear differential amplification algorithm for detecting and locating stationary PES outliers and a handling algorithm for controlling DASD operations with detected stationary PES outliers; said algorithms performed by said PES classifier including the steps of: obtaining a plurality of PES samples, said plurality of PES samples obtained from a plurality of servo sectors around a track; utilizing said PES samples, computing a normalized outlier value for said plurality of servo sectors; sequentially storing said computed normalized outlier values; comparing said sequentially stored normalized outlier values with a set threshold value; identifying a stationary PES outlier responsive to each said stored outlier value being greater than said set threshold value; and utilizing each said identified stationary PES outlier during predefined operations of the DASD.
16. Apparatus for implementing enhanced performance in the presence of stationary position error signal (PES) outliers as recited in claim 15 wherein said PES classifier includes a processor in the DASD.
17. Apparatus for implementing enhanced performance in the presence of stationary position error signal (PES) outliers as recited in claim 16 wherein said PES classifier processor is a digital signal processor.
18. Apparatus for implementing enhanced performance in the presence of stationary position error signal (PES) outliers as recited in claim 15 wherein said handling algorithm for controlling DASD operations with detected stationary PES outliers is active during predefined operations of the DASD including recalibration or error recovery operations.
19. A computer program product for implementing enhanced performance in the presence of stationary position error signal (PES) outliers in a disk drive, said computer program product including a plurality of computer executable instructions stored on a computer readable medium, wherein said instructions, when executed by a PES classifier processor, cause the PES classifier processor to perform the steps of: obtaining a plurality of PES samples, said plurality of PES samples obtained from a plurality of servo sectors around a track; utilizing said PES samples, computing a normalized outlier value for said plurality of servo sectors; sequentially storing said computed normalized outlier values; comparing said sequentially stored normalized outlier values with a set threshold value; and identifying a stationary PES outlier responsive to each said stored outlier value being greater than said set threshold value.
Cooperative Patent Classification codes for this invention. Click any code to explore related patents in that topic.
June 4, 2001
March 2, 2004
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